Tag Archives: engineer

If I am an architect, a designer, an engineer or even BIM manager – Will a Robot take my job? This is the big question I recently presented in my talk at RTC Australia as part of the session BIMx: Big Ideas around Big Data. Open up my slideshare presentation above that accompanies this blog post.

NESTA, a UK innovation charity has a quiz you can take to see if a robot is likely to take your job. The quiz asks a series of 6 questions around skills and ongoing learning, if you manage complex real world tasks, work with, teach and manage people, or design and manage technology, machines and systems. It uses your answers to determine how likely it is a robot would take your job.

The answer is that an architect is “Robot Proof” with a low probability of a robot taking our job. BUT does this match with our experience? Are architects, engineers, or designers really likely to be robot proof?

Whilst we think a robot won’t take our job – what about a computer?

Many of us would agree that BIM has already resulted in smaller project teams. Computers have long been a part of the design process. Whilst we often forget CAD standards for ‘computer aided design’, computers can now aid the design process in much more significant ways than back when AutoCAD was released. Its interesting though that today a google search of computer generated architecture still mostly generates links related to rendering and imagery, rather than designs produced by computers.

If you think that BIM won’t take your job – what about Big Data? We are already using data to check, verify and evaluate options within our designs. As the scale of the data available gets ever bigger these processes become more complex and more powerful. Right now google searching for data generated architecture won’t get you many hits related to buildings, but this is sure to soon change.

Rules based checking might not yet be big data. But it is about using data sources to validate designs or documentation. Examples include checking codes or standards using software such as solibri.

Again data analysis doesn’t necessarily mean big data yet. Analysis began as something that architects did using pen and paper, a site analysis diagram for example. Data analysis is starting to become more computer driven which allows for much more significant analysis to take place. Examples include environmental or performance analysis of buildings, or analysis on a larger city scale looking at land use and traffic patterns. This kind of analysis is very much in the realm of current uses for big data.

Data is also the basis of simulations. For example fire or traffic simulation modelling is based upon creating algorithms from data. Currently the simulations used within the AEC industry are relatively simple algorithims.
Big data gives the potential for developing significantly more complex simulations. Last year at RTC in Chicago I discussed the potential for big data to allow us to simulate human behaviour in complex building types such as workspaces with the potential of increasing a companies productivity. (see blog post here)

So, data can evaluate design – but could big data actually drive design? Is it already happening? As with data based checking, its certainly true that data driven design exists already – and has for some time, although generally not yet into the possibilities of big data. Computational and generative design is data based upon algorithms and therefore data based design. Algorithms are already being used for design in many different ways.

The use of formulas to create design is an example of data driven design.
An example is the façade of the Auckland Savings Bank by BVN and Jasmax which was designed using Microsoft Excel and the Chaos formula.

The structure of the Watercube by PTW and Arup was designed using an algorithm to determine structural steel member sizes.

A simulation is just another kind of algorithm. Rather than just using simulations to test current design proposals, the simulation algorithims can be part of the design software and the design options can be based upon the outcomes of the simulations. This bandstand by UK architects Flanagan Lawrence was designed using Dynamo and an acoustic simulation algorithm called acoustamo.

Algorithms can be used to optimise an existing design. At the Barclays Centre by ShoP – detailed design of the steel panels was undertaken using CATIA to generate options which allowed a reduction from 230,000 sqm of steel to 150,000sqm. No two of the 12,000 panels are the same.

This exhibition hall building was designed by the University of Stuttgart’s Institute for computational design.

The question – How can you create a resilient timber structure with as little material as possible? This is a simple example of applying one rule to a simple building type. Using an algorithm inspired by a sand dollar one of natures most efficient structures, this building was designed by computer. The human input to the design is the initial idea and the design of the algorithms. (Read more)
As a side note, it was built by robots too.

What about more complexity? The complexity of trees growing in nature? There is actually already an algorithm for that. The programming to create suburban housing exists too (its initial use is for generating realistic houses for 3d gaming environments). Using rules based criteria such as number of rooms, adjacencies and architectural style, a suburb of varied housing can be produced.

With big data the questions and the building programs can get more complex. And these kinds of design tools are not as far away as you might think. Autodesk has a lab project in development called Dreamcatcher. “Dreamcatcher is a goal-directed design system that enables designers to input specific design objectives, including functional requirements, material type, manufacturability, performance criteria, and cost restrictions. The infinite computing power of the cloud then takes over.” The publicity for Autodesk’s Project Dreamcatcher suggests it is for industrial design – the same could potential apply to create rules based design solutions for buildings.

Autodesk are not the only company investing in this technology. Google has setup a spinoff called Flux to explore how data will shape our future. Right now Flux software and much of the media is focused on the metro scale data analysis but the future of Flux is about buildings.

Flux asks “What would happen if we stopped designing individual buildings and started designing building seeds” It is based upon the idea that the data will form seeds.

The information would include the codes, standards, weather conditions, occupant data, building product data and other information available about a building, its site, its occupants and client requirements as well as industry data such as materials, systems and construction methods and costs.

Just as each seed grows up to be a different tree, the building data seeds will grow to be different buildings depending upon the site and its constraints, the client requirements and other project specific inputs.
This kind of design will have a significant impact upon the way our industry operates. (See post by Randy Deutsch)

This is a clip from a talk by Jen Carlilse co-founder of Flux. (Embeded in slide share or at youtube)

We probably all agree that the building examples in the Flux video are somewhat lacking in the architectural beauty department. If nature could be an algorithm – could beauty also be an algorithm? Is there the possibility that in the future we could use data analysis to design beauty into our buildings, to use data to design buildings like the Sydney Opera House?

So what will my job be? It won’t be drafting disabled toilets anymore that’s for sure.

I’d like to think that the data will allow us to get rid of the drudgery. It will allow us to focus on the best parts of our jobs. It will allow us to realise the true value of design.

We will still evaluate the computer options and talk to the clients. Whilst data can assist us to make decisions, the human race is not about to let everything be decided purely on the basis of data – if we did we would be doing it already. Human nature is that we still want humans involved in decision making. We still need to tell the computers what to do at some level. Does it mean we all become programmers rather than architects and engineers? Could this process can bring out the best in both humans and computers?